R interface to DSDP semidefinite programming library. The DSDP software is a free open source implementation of an interior-point method for semidefinite programming. It provides primal and dual solutions, exploits low-rank structure and sparsity in the data, and has relatively low memory requirements for an interior-point method.

This package implements methods described by the paper Robins and Tsiatis (1991) <DOI:10.1080/03610929108830654>. These use g-estimation to estimate the causal effect of a treatment in a two-armed randomised control trial where non-compliance exists and is measured, under an assumption of an accelerated failure time model and no unmeasured confounders.

The tools and utilities to estimate the model described in "Gremlin's in the Data: Identifying the Information Content of Research Subjects" (Howell et al. (2021) <doi:10.1177/0022243720965930>) using conjoint analysis data such as that collected in Sawtooth Software's Lighthouse or Discover products. Additional utilities are included for formatting the input data.

R Commander plugin for teaching statistical methods. It adds a new menu for making easier the teaching of the main concepts about the main statistical methods.

Functionality to download stock prices, cryptocurrency data, and more from the Tiingo API <https://api.tiingo.com/>.

This package contains functions to generate random numbers from the beta distribution and random vectors from the Dirichlet distribution.

Extracts tagged text from markdown manuscripts for inclusion in dynamically generated revision letters. Provides an R markdown template based on papaja::revision_letter_pdf() with comment cross-referencing, a system for managing multiple sections of extracted text, and a way to automatically determine the page number of quoted sections from PDF manuscripts.

This package creates a numeric guide for writing the formula for the determinant of a square matrix (a detguide) as a function of the elements of the matrix and writes out that formula, the symbolic representation.

Plays the game of Snakes and Ladders and has tools for analyses. The tools included allow you to find the average moves to win, frequency of each square, importance of the snakes and the ladders, the most common square and the plotting of the game played.

This package implements an extension of the Generalized Berk-Jones (GBJ) statistic for survival data, sGBJ. It computes the sGBJ statistic and its p-value for testing the association between a gene set and a time-to-event outcome with possible adjustment on additional covariates. Detailed method is available at Villain L, Ferte T, Thiebaut R and Hejblum BP (2021) <doi:10.1101/2021.09.07.459329>.

An interactive charting library built on Svelte and D3 to easily produce SVG charts in R. Designed to simplify shiny development by eliminating the need for renderUI(), insertUI(), removeUI(), and shiny proxy functions, using Svelte''s reactive state system instead.

This package provides functions for tabulating and summarizing categorical, multiple response, ordinal, and continuous variables in R data frames. Makes it easy to create clear, structured summary tables, so you spend less time wrangling data and more time interpreting it.

Identify 17 Sustainable Development Goals and associated 169 targets in text.

This package provides a computational framework for identification of B cell clones from Adaptive Immune Receptor Repertoire sequencing (AIRR-Seq) data. Three main functions are included (identicalClones, hierarchicalClones, and spectralClones) that perform clustering among sequences of BCRs/IGs (B cell receptors/immunoglobulins) which share the same V gene, J gene and junction length. Nouri N and Kleinstein SH (2018) <doi: 10.1093/bioinformatics/bty235>. Nouri N and Kleinstein SH (2019) <doi: 10.1101/788620>. Gupta NT, et al. (2017) <doi: 10.4049/jimmunol.1601850>.

Sometimes it is useful to serve up alternative shiny UIs depending on information passed in the request object, such as the value of a cookie or a query parameter. This packages facilitates such switches.

Import, process, summarize and visualize raw data from metabolic carts. See Robergs, Dwyer, and Astorino (2010) <doi:10.2165/11319670-000000000-00000> for more details on data processing.

Routines for creating, manipulating, and performing Bayesian inference about Gaussian processes in one and two dimensions using the Fourier basis approximation: simulation and plotting of processes, calculation of coefficient variances, calculation of process density, coefficient proposals (for use in MCMC). It uses R environments to store GP objects as references/pointers.

Catch advice for data-limited vertebrate and invertebrate fisheries managed by harvest slot limits using the SlotLim harvest control rule. The package accompanies the manuscript "SlotLim: catch advice for data-limited vertebrate and invertebrate fisheries managed by harvest slot limits" (Pritchard et al., in prep). Minimum data requirements: at least two consecutive years of catch data, lengthâ frequency distributions, and biomass or abundance indices (all from fishery-dependent sources); species-specific growth rate parameters (either von Bertalanffy, Gompertz, or Schnute); and either the natural mortality rate ('M') or the maximum observed age ('tmax'), from which M is estimated. The following functions have optional plotting capabilities that require ggplot2 installed: prop_target(), TBA(), SAM(), catch_advice(), catch_adjust(), and slotlim_once().

This package provides a simple progress bar to use for basic and advanced users that suits all those who prefer procedural programming. It is especially useful for integration into markdown files thanks to the progress bar's customisable appearance.

This package implements the Symphony single-cell reference building and query mapping algorithms and additional functions described in Kang et al <https://www.nature.com/articles/s41467-021-25957-x>.

Output colors used in literal vectors, palettes and plot objects (ggplot).

Facilitates secret management by storing credentials in a dedicated file, keeping them out of your code base. The secrets are stored without encryption. This package is compatible with secrets stored by the SecretsProvider Python package <https://pypi.org/project/SecretsProvider/>.

Routines to write, simulate, and validate stock-flow consistent (SFC) models. The accounting structure of SFC models are described in Godley and Lavoie (2007, ISBN:978-1-137-08599-3). The algorithms implemented to solve the models (Gauss-Seidel and Broyden) are described in Kinsella and O'Shea (2010) <doi:10.2139/ssrn.1729205> and Peressini and Sullivan (1988, ISBN:0-387-96614-5).

Remove batch effects by projecting query batches into the reference batch space.